Agronomy, Volume 14, Issue 4 (April 2024) – 236 articles

A numerical simulation model of a natural ventilation greenhouse is helpful for improving the production and quality of greenhouse crops in tropical areas. Field experiments show that the mean coefficient of variation of indoor light intensity in four seasons was lower than 10.0%. The highest indoor temperature reached 39.3 °C during summer, while the average indoor temperature ranged from 24 °C to 26 °C in the other three seasons. The average relative humidity in the greenhouse ranged from 76% to 87% annually, which was higher and more stable than that in the external environment. A three-dimensional steady-state numerical model of the greenhouse was established based on computational fluid dynamics. Under natural ventilation conditions, the maximum error between the simulated value and the measured value of the temperature in each measuring point was 5.90%. And the average relative error between the simulated and measured values was 3.0% in the range of 0.7−1.5 m of crop cultivation height. Finally, a numerical simulation of adding side windows and expanding the vents was carried out. The results show that these methods can homogenize the airflow distribution in the greenhouse and improve the utilization efficiency of natural ventilation without more mechanical system operations. Full article

Crop sequence and tillage can affect the yield of peanut (Arachis hypogaea L.) and other crops. Research was conducted from 2006 through 2022 to determine the response of peanut to previous crop sequences including corn (Zea mays L.) and cotton (Gossypium hirsutum L.) planted in continuous conventional tillage (e.g., disking, field cultivating, and bedding with in-row sub-soiling) or strip tillage (e.g., tilling a 45 cm section on rows spaced 91 cm apart using fluted coulters, rolling baskets, and in-row sub-soiling). In 2013, 2019, and 2022, the entire test area was planted with peanut. In 2019 and 2022, peanut was planted without or with fluopyram applied in the seed furrow at planting. Decreasing the number of years between peanut planting resulted in lower peanut yields compared with fewer years of peanut planting in the rotation sequence. Continuous conventional tillage and strip tillage resulted in similar peanut yields at one location, while the yield was lower at a second location when peanut was planted in continuous strip tillage. Fluopyram did not affect peanut yield regardless of previous crop rotation sequence, the number of years separating peanut plantings, or the tillage system. However, minor differences in the populations of plant-parasitic nematodes in soil were noted when comparing fluopyram treatment. The results from these experiments indicate that while fluopyram can reduce the populations of some plant-parasitic nematodes in soil, the magnitude of reduction does not translate into increases in peanut yield. Full article

Establishing lucerne field is an efficient way to protect natural steppes, alleviate conflicts between meadows and livestock, and promote the development of animal husbandry. However, problems such as extensive field management, valuing yield over quality, and low resource utilization are endemic in production. Exploring reasonable cultivation patterns can contribute to improving the current situation of artificial grassland production and promoting the high-quality development of husbandry and prataculture. Lucerne the field experiment was carried out in Jingtai, Gansu Province, China in 2021–2022; this study compared and analyzed the effects of three cultivation patterns—ridge tillage with plastic film mulching (PM), ridge tillage with biodegradable film mulching (BM), and traditional flat planting (FP)—on soil water, heat, and fertilizer, as well as lucerne growth, yield, quality, and water and nitrogen use efficiency. The results show that: (1) during the growth period of lucerne, PM and BM treatments augment the average moisture content of the soil layer of 0–120 cm by 31.19% and 24.03% compared to the FP treatment, respectively. In the soil layer of 0–40 cm, PM and BM treatments abate the soil moisture content of the ridges by an average of 19.29% and 7.89% compared to that in the ditches, respectively. In the soil layer of 40–120 cm, PM and BM treatments elevate the soil moisture content of the ridges by 4.40% and 4.65% on average compared to that in the ditches, respectively. The average soil temperature in a soil layer of 5–25 cm shows PM > BM > FP. In contrast with the FP treatment, PM and BM treatments increase the soil temperature of the ridges by an average of 1.87 °C and 0.96 °C and decrease that of the ditches by an average of 0.47 °C and 0.46 °C, respectively. After two years of planting, the three cultivation patterns all promote the soil nutrient content. Compared to the FP treatment, PM and BM treatments increase the organic matter content by 9.94% and 19.94%, respectively. (2) Ridge tillage with film mulching can evidently stimulate the growth of lucerne and enhance yield and quality. Compared to the FP treatment, PM and BM treatments enhance plant height by an average of 15.37% and 4.04%, stem diameter by an average of 34.14% and 14.58%, yield by an average of 21.20% and 14.77%, crude protein content by an average of 13.47% and 7.68%, and relative feed value by an average of 8.71% and 4.41%, respectively. (3) During the two-year growing period, the irrigation amount of lucerne was 508.60–615.30 mm, and the evapotranspiration was 563.70–761.80 mm. Compared to the FP treatment, PM and BM treatments hoist water use efficiency by an average of 43.50% and 17.56%, nitrogen partial factor productivity by an average of 21.20% and 15.22%, and net income by an average of 14.78% and 11.05%, respectively. In summary, in ridge tillage, both ordinary film mulching and biodegradable film mulching can create a favorable soil environment for lucerne growth and heighten production effect. The former has a better effect on advancing the lucerne production effect, and the latter exhibits superior performance in improving soil fertility. Full article

The phytochrome-interacting factor (PIF) proteins are part of a subfamily of basic helix–loop–helix (bHLH) transcription factors that integrate with phytochromes (PHYs) and are known to play important roles in adaptive changes in plant architecture. However, the characterization and function of PIFs in potatoes are currently poorly understood. In this study, we identified seven PIF members in potatoes and named them StPIF01-1, StPIF01-2, StPIF03, StPIF06-1, StPIF06-2, StPIF07, and StPIF09 based on their location in potato chromosomes. The chromosomal location, gene structures, physicochemical characteristics, phylogenetic tree, and tissue-specific expression of StPIFs were also analyzed. RT-qPCR analysis revealed that the StPIF3 gene was highly induced by shade and may play a crucial regulatory role in potato responses to shade stress. Also, multiple cis-regulatory elements involved in light response were detected in the promoter of the StPIF genes. Subcellular localization analysis indicated that the StPIF3-encoding protein is mainly localized in the nucleus. Transgenic overexpression of StPIF3 in potatoes increased stem length, chlorophyll accumulation, and enhanced shade-avoidance symptoms, whereas the StPIF3-interfering lines had a lower plant height and more chlorophyll accumulation. These findings enhance our comprehension of StPIF gene roles, potentially advancing potato yield and quality research. This study provides detailed information about StPIFs and identifies the function of StPIF3, which is involved in shade-avoidance syndrome. Full article

The content of protein and oil in soybeans is an important trait for evaluating quality and is regulated by genetic and environmental factors, lacking comprehensive identification under a variety of ecological conditions. Therefore, evaluating the stability of soybean quality traits under different environmental conditions has great significance for various applications. In this study, we compare 150 soybean varieties from Northeast China (Group A and Group B) and the Huang-Huai-Hai region (Group C). As the release time progressed, the oil content in the soybean varieties showed an upward trend in both Northeast China and the Huang-Huai-Hai region, while the protein content showed a downward trend. Additionally, the oil contents were negatively correlated with the protein contents and the sum of protein and oil contents, while the protein contents were positively correlated with the sum of protein and oil contents, with the correlation becoming stronger as the latitude decreased. Moreover, there were obvious variations in quality stability among different varieties. Hefeng 45, Jilinxiaolidou 4, and Zhonghuang 19 had relatively high protein contents and exhibited good stability across different environments, while Kenjiandou 25, Changnong 17, Dongnong 46, Kennong 17, Liaodou 14, and GR8836 had relatively high oil contents with good stability performance in varying environments. Full article

The microclimate environment can be conveniently controlled with accuracy by plant incubators, in which the cuttings propagation method can efficiently enhance seedling production. To ensure air flow evenly throughout the incubator, the scientific design of the air inlet is crucial. This study utilized a computational fluid dynamics (CFD) model to simulate the airflow patterns in a culture layer under different air inlet conditions. Furthermore, the optimal design parameters were determined by way of response surface methodology (RSM) and the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Adopting the optimal parameters, a prototype was manufactured, and a cuttings experiment was carried out with apple cuttings in the incubator. The results showed that the optimal air inlet radius is 90 mm, the optimal air inlet height is 188 mm, and the optimal uniform flow plate hole diameter is 13 mm. Meanwhile, the apple cuttings were able to root. Therefore, this incubator with optimal parameters can be used for cuttings. The study provides a methodological and theoretical basis for the future optimizing of air inlet parameters and promoting cuttings rooting. Full article

The scientific aim of this article is to elucidate the effects of various tillage practices on soil properties and crop yields; additionally, it seeks to highlight the significant potential of specific farming systems in enhancing soil organic carbon, thereby positively influencing CO₂ emissions from soil. In the experimental station of Vytautas Magnus University, Kaunas District, Lithuania (54°52′50″ N and 23°49′41″ E), a long-term field experiment has been established since 1999, and studies have been conducted since 2003. The soil of the experimental site is classified as Epieutric Endocalcaric Planosol (Endoclayic, Episiltic, Aric, Drainic, Endoraptic, Uterquic), according to the World Reference Base (WRB, 2022). Two primary factors were assessed. Factor A incorporated practices of straw removal versus straw chopping and spreading, while Factor B evaluated a spectrum of tillage techniques: conventional deep plowing and two no-tillage practices, one of which involved cover crops. The findings from this long-term study highlight a significant increase in SOC stocks across all treatments over the 20-year period. Notably, the no-tillage practices, coupled with the spreading of chopped straw, demonstrated the most substantial growth in SOC levels, particularly in the top 0–10 cm soil layer. This trend underscores the effectiveness of minimizing soil disturbance and incorporating organic matter in boosting SOC stocks. The different tillage systems influence CO₂ emissions from soil. Initially, direct sowing into uncultivated land, both with and without cover crops, led to a notable reduction in CO₂ emissions compared to conventional plowing. However, this effect was found to vary over the growth cycle of the plant, highlighting the dynamic interaction between tillage practices, soil properties, and environmental conditions. Collaborative research efforts that involve farmers, scientists, policymakers, and other stakeholders are crucial for the development of holistic, practical, scalable solutions that enhance the sustainability and productivity of agricultural systems. This study contributes to the growing body of knowledge on sustainable agriculture, providing insights for farmers, agronomists, and policymakers in their quest to promote environmentally sound and productive agricultural systems. Full article

Soil carbon content and stability are primarily influenced by the stabilization of particulate organic matter (POM) and mineral-associated organic matter (MAOM). Despite extensive research on the stabilization processes of POM and MAOM carbon components under various land-use types, the investigation into stabilization processes of soil carbon remains limited in saline–alkali soils. Therefore, we collected soil samples from different positions of saline–alkali drainage ditches at four reclamation times (the first, seventh, fifteenth, and thirtieth year) to determine their carbon content and physicochemical properties. Moreover, POM and MAOM fractions were separated from soil samples, and Fourier transform infrared spectra (FTIR) were used to investigate changes in their chemical composition. The results showed that with increasing reclamation time, the soil total carbon and soil organic carbon (SOC) contents significantly increased from 14 to 15 and 2.9 to 5.5 g kg⁻¹, respectively. In contrast, soil inorganic carbon content significantly decreased from 11 to 9.6 g kg⁻¹. Notably, the changes in soil carbon components following the increasing reclamation time were primarily observed in the furrow sole at a depth of 20–40 cm. While the SOC content of the POM fraction (SOC_POM) decreased significantly, the SOC content of the MAOM fraction (SOC_MAOM) increased significantly. These alterations were largely dominated by drainage processes after reclamation instead of a possible conversion from SOC_POM to SOC_MAOM. FTIR results revealed that MAOM was greatly influenced by the reclamation time more than POM was, but the change in both POM and MAOM contributed to an increase in soil carbon stability. Our findings will deepen the comprehension of soil carbon stabilization processes in saline–alkali drainage ditches after reclamation and offer a research framework to investigate the stability processes of soil carbon components via alterations in POM and MAOM fractions. Full article

In rice cultivation and breeding, obtaining accurate information on the quantity and spatial distribution of rice plants is crucial. However, traditional field sampling methods can only provide rough estimates of the plant count and fail to capture precise plant locations. To address these problems, this paper proposes P2PNet-EFF for the counting and localization of rice plants. Firstly, through the introduction of the enhanced feature fusion (EFF), the model improves its ability to integrate deep semantic information while preserving shallow spatial details. This allows the model to holistically analyze the morphology of plants rather than focusing solely on their central points, substantially reducing errors caused by leaf overlap. Secondly, by integrating efficient multi-scale attention (EMA) into the backbone, the model enhances its feature extraction capabilities and suppresses interference from similar backgrounds. Finally, to evaluate the effectiveness of the P2PNet-EFF method, we introduce the URCAL dataset for rice counting and localization, gathered using UAV. This dataset consists of 365 high-resolution images and 173,352 point annotations. Experimental results on the URCAL demonstrate that the proposed method achieves a 34.87% reduction in MAE and a 28.19% reduction in RMSE compared to the original P2PNet while increasing $R^2$ by 3.03%. Furthermore, we conducted extensive experiments on three frequently used plant counting datasets. The results demonstrate the excellent performance of the proposed method. Full article

Low-density polyethylene (LDPE) mulching films have an important function in crop cultivation; at the end of their life, however, their removal and disposal become both an economic and environmental problem. One possible alternative to low-density polyethylene (LDPE) mulch is provided by certified soil-biodegradable mulch films, such as those produced by Novamont and commercially available under the trade name MaterBi^®. MaterBi is a biodegradable thermoplastic material made with starch and a biodegradable copolyester based on proprietary technology. In this study, we compared two biodegradable MaterBi^®-based films (commercial and experimental films) with bare soil and a low-density polyethylene to evaluate their effect on yield and on a number of qualitative characteristics (organoleptic and nutraceutical composition) of eggplant fruits (cv Mirabelle F1) grown in two different regions in Southern Italy (Sicily and Campania). In our study, the use of biodegradable MaterBi^® films improved not only yield and production parameters, such as the number and average weight of fruits, but also lipophilic and hydrophilic antioxidant activity and phenolic and ascorbic acid content. For many parameters, responses differed according to the cultivation environment and, in particular, the site’s pedoclimatic conditions. Our results suggest that biodegradable MaterBi^®-based mulching films are a potentially valid alternative to traditional LDPEs, providing the production and quality benefits reported above and promoting environmental sustainability, thanks to their positive biodegradable properties. Full article

Conventional fertilizer management can destroy the structure of soil. Replacing chemical fertilizers with organic fertilizers can improve soil quality and nitrogen use efficiency. We aimed to study the effects of organic fertilizer substitutions for chemical nitrogen fertilizer on soil fertility and nitrogen use efficiency in order to clarify the effectiveness of the available nutrient management measures in improving soil quality and increasing foxtail millet yield. A field experiment was carried out over two consecutive years, and a total of six treatments were set up: no fertilizer (CK), chemical nitrogen fertilizer alone (N), the substitution of 25% of chemical nitrogen fertilizer with bio-organic fertilizer (N25A1), the substitution of 25% of chemical nitrogen fertilizer with fermented mealworm manure (N25B1), the substitution of 50% of chemical nitrogen fertilizer with bio-organic fertilizer (N50A2), and the substitution of 50% of chemical nitrogen fertilizer with fermented mealworm manure (N50B2). The results of this study show the following: (1) Compared with chemical nitrogen fertilizer, the substitution of organic fertilizer for nitrogen fertilizer reduced the bulk density and solid phase of the soil, and it increased the total porosity, water content, liquid phase, and gas phase of the soil. (2) Compared with nitrogen fertilizer, the use of an organic fertilizer increased the contents of nitrate nitrogen, ammonium nitrogen, and total nitrogen in the soil by 13.59~52.56%, 4.47~18.27%, and 4.40~12.09%, respectively. The content of alkaline nitrogen increased by 1.70~32.37%, and the contents of soil available potassium, available phosphorus, and organic matter also increased. (3) The activities of sucrase, urease, glutaminase, and asparaginase were improved by replacing chemical nitrogen fertilizer with organic fertilizer. The N25 treatments performed better than the N50 treatments, and fermented mealworm manure performed better than biological organic fertilizer. (4) A moderate application of organic fertilizer (N25) can increase the grain yield, ear weight, grain weight, and 1000-grain weight of foxtail millet, whereas excessive application of organic fertilizer (N50) can reduce foxtail millet yield. (5) Replacing chemical nitrogen fertilizer with organic fertilizer can improve the agronomic use efficiency, physiological efficiency, biased productivity, harvest index, and apparent use efficiency of nitrogen fertilizer. In this study, the substitution of 25% of chemical nitrogen fertilizer with fermented mealworm manure was the best combination for restoring crop productivity and soil quality. Full article

Starch extraction from tubers and roots has long been an essential process, playing a crucial role in diverse industries ranging from alimentary to pharmacology. This review explores the different methods employed in starch extraction, including traditional techniques and the most innovative mechanical strategies. The methods show a good improvement in many aspects, such as an improvement in the efficiency of the process and an improvement in the yield, showing a value of 10.0–65.0% depending on the starch source. On the other hand, solvents such as NaOH are used in many mechanical processes for alkaline digestion to improve the extraction time. Ethanol and K₂S₂O₅ concentrations of 0.5% and 0.8% were used to prevent oxidation and modify some properties of the extracted starch. The use of many solvents has improved the optimization of the processes, providing the final extracted starch with more advantages and better quality. However, using enzymes such as cellulase in new and innovative ways has provided more advantages and a better efficiency and yield than the other methods. Each method has its advantages and challenges, highlighting the importance of understanding the diversity of different approaches and their impact on the yield, sustainability, environmental considerations, and quality of the extracted starch. As the world looks for more ecological approaches, this review shows the importance of critically evaluating the yield, efficiency, and environmental implications of the extraction methods, providing us with more ways of evaluating the methods used for starch extraction. The ecological impact is a crucial point when evaluating the innovation of a new extraction process, which is why methods such as ultrasound and pulsed electric-field-assisted techniques have been proposed. These methods have been presented as sustainable techniques called green technologies, offering more approaches and different advantages than the other methods. This review intends to investigate the complexities and considerations of starch extraction, providing a solid basis for decision-making regarding starch extraction. In a time where sustainability and product quality are crucial elements of industrial strategy formulation, an in-depth understanding of these methods becomes imperative to the development of responsible practices and efficiency in starch extraction. Full article

The significance of environmental considerations has been highlighted by the substantial impact of plant pests on ecosystems. Addressing the urgent demand for sophisticated pest management solutions in arboreal environments, this study leverages advanced deep learning technologies to accurately detect and classify common tree pests, such as “mole cricket”, “aphids”, and “Therioaphis maculata (Buckton)”. Through comparative analysis with the baseline model ResNet-18 model, this research not only enhances the SE-RegNetY and SE-RegNet models but also introduces innovative frameworks, including GCT-Inception-ResNet-V3, SE-Inception-ResNet-V3, and SE-Inception-RegNetY-V3 models. Notably, the GCT-Inception-ResNet-V3 model demonstrates exceptional performance, achieving a remarkable average overall accuracy of 94.59%, average kappa coefficient of 91.90%, average mAcc of 94.60%, and average mIoU of 89.80%. These results signify substantial progress over conventional methods, outperforming the baseline model’s results by margins of 9.1%, nearly 13.7%, 9.1%, and almost 15% in overall accuracy, kappa coefficient, mAcc, and mIoU, respectively. This study signifies a considerable step forward in blending sustainable agricultural practices with environmental conservation, setting new benchmarks in agricultural pest management. By enhancing the accuracy of pest identification and classification in agriculture, it lays the groundwork for more sustainable and eco-friendly pest control approaches, offering valuable contributions to the future of agricultural protection. Full article

Insect recognition, crucial for agriculture and ecology studies, benefits from advancements in RGB image-based deep learning, yet still confronts accuracy challenges. To address this gap, the HI30 dataset is introduced, comprising 2115 hyperspectral images across 30 insect categories, which offers richer information than RGB data for enhancing classification accuracy. To effectively harness this dataset, this study presents the Two-Branch Self-Correlation Network (TBSCN), a novel approach that combines spectrum correlation and random patch correlation branches to exploit both spectral and spatial information. The effectiveness of the HI30 and TBSCN is demonstrated through comprehensive testing. Notably, while ImageNet-pre-trained networks adapted to hyperspectral data achieved an 81.32% accuracy, models developed from scratch with the HI30 dataset saw a substantial 9% increase in performance. Furthermore, applying TBSCN to hyperspectral data raised the accuracy to 93.96%. Extensive testing confirms the superiority of hyperspectral data and validates TBSCN’s efficacy and robustness, significantly advancing insect classification and demonstrating these tools’ potential to enhance precision and reliability. Full article

Climate change requires the introduction of alternative crops in certain temperate areas due to the warmer and drier growing seasons. Maize, one of the most important crops, is projected to become less tolerant of a drier climate. Therefore, it is necessary to find an alternative species that is less susceptible to environmental stressors. This study compared the germination, growth vigour, and stress tolerance of maize and sorghum grow in six types of soil under three water regimes. The results indicate that sorghum germination is faster and more uniform. The most significant differences in germination rates were found in chernozem (88.9% and 72.2% for sorghum and maize, respectively) and saline solonetz (74.4% and 63.3% for sorghum and maize, respectively). Maize exhibited higher growth vigour only in three cases, i.e., under solonetz–flooding, shifting sand–drought, and brown forest floor–flooding conditions. An ANOVA showed a significant difference between sorghum and maize stress conditions due to soil conditions and water availability (p < 0.0001). Sorghum can be a suitable alternative to maize, but only in areas with hot, dry periods and in areas where the soil is not too prone to waterlogging, regardless of its quality. Full article

Increasing the use of organic fertilizers is an effective measure to improve, increase soil fertility and maintain crop yields. The aim of this study was to investigate the influence of different types of organic fertilizers on the early yield of grapes and soil parameters, as well as the relationship between soil parameters and grape yield under fertilization conditions. The ‘Shine Muscat’ grape was used as the material, with early maturing cultivation in the solar greenhouse. From the time of grape planting, three-year continuous fertilization management was carried out using five types of base fertilizers: chemical fertilizer (CK), fermented corn stalk residue (A1), mature sheep manure (A2) and two types of commercial organic fertilizers (B1 and B2). In the third year, berry and soil samples were collected to determine grape yield and evaluate soil physicochemical properties, nutrient status and changes in enzyme activity, studying the relationship between grape yield and soil indicators. The results show that compared to CK, the grape yields with B1 and B2 increased by 19.04% and 16.26%, respectively, while A1 and A2 decreased by 24.09% and 18.97%. Organic fertilizer application reduced soil bulk density, increased soil porosity, enhanced soil organic matter content and effectively buffered soil pH levels. Two types of commercial fertilizers (B1 and B2) improved soil total nitrogen, total phosphorus, total potassium, available nitrogen and available phosphorus content to varying degrees. All organic fertilizer treatments effectively increased soil enzyme activity, except for soil sucrase activity. Through correlation and regression analyses, it was found that in this study, the levels of available nitrogen, available potassium and soil saccharase activity were most closely related to early grape yield. Their influence on grape yield was in the order of available nitrogen > soil saccharase activity > available potassium. Therefore, with a combined organic and inorganic basal fertilization system, the fertilizer nutrients are more comprehensive and help to increase the productivity of grapes at the beginning of the fruiting period. Nitrogen and phosphorus are very important in the maintaining of grape yields and improving sucrose activity in the soil through the application of organic fertilizers cannot be ignored when increasing yields. Full article

One biostrategy to boost the sustainability of strawberry cultivation is the application of biostimulants to the growing substrate. Here, we investigated whether the use of biostimulants and their combinations affects the strawberry plants’ phyllochron, phenology, and fruit quality. We tested the absence (control) and presence of biostimulants (arbuscular mycorrhizal fungi (AMF), Ascophyllum nodosum (AN), Trichoderma harzianum (TH), AMF + AN, AMF + TH, AN + TH, and AMF + AN + TH). The experimental design used was in completely randomized blocks (four replications). AMF was represented by a multi-species on-farm inoculant; A. nodosum was represented by the commercial product Acadian^®; and T. harzianum was represented by the commercial product Trichodermil^®. The leaf emission rate, the occurrence and duration of phenological stages, and fruit quality were assessed. The greatest precocity in terms of harvesting the first fruit was observed in plants grown with AMF + TH, which also had the lowest phyllochron (77.52 °C day·leaf⁻¹). Those treated only with AMF were the latest (144.93 °C day·leaf⁻¹). More flavorful fruits were produced by plants grown with AMF + TH. Plants inoculated with the AMF community, whether or not associated with A. nodosum and T. harzianum, had more than 94% mycorrhizal colonization. We conclude that AMF, A. nodosum, T. harzianum, and their combinations influence the phenology, phyllochron, and fruit quality of strawberry plants. In the growing conditions of the Brazilian subtropics, the AMF and T. harzianum combination shortens the strawberry cycle, from transplanting the daughter plants to harvesting the first fruit, and improves the fruit flavor. Full article

Alfalfa is one of the most widely cultivated perennial legume crops used as feedstock for animals. Efficiently estimating alfalfa yield and quality traits before harvesting is critical for the decision-making process regarding precision management activities and harvesting time to ensure high profitability. Satellite-based radar is a powerful tool in remote sensing for crop monitoring because it provides high-quality data regardless of weather conditions. Therefore, this study aims to investigate the potential use of satellite radar features and environmental factors in estimating alfalfa yield and quality. Alfalfa yield and quality traits, including dry matter yield (DMY), crude protein (CP), neutral detergent fiber (NDF), NDF digestibility (NDFD), and acid detergent fiber (ADF), were collected over 16 alfalfa fields from 2016 to 2021, leading to 126 samples in total. Sentinel-1 radar backscattering coefficients and environmental factors were collected for all the fields across all growing seasons. Five commonly used machine learning models were established to estimate each alfalfa trait separately. The results show that the Extreme Gradient Boosting model consistently performed the best for all alfalfa traits. The accuracy of the DMY estimates is acceptable, with an average R² of 0.67 and an RMSE of 0.68 tons/ha. The best result for estimating CP was an average R² of 0.70 and an RMSE of 1.63% DM. In estimating alfalfa fiber indicators (i.e., ADF, NDF, and NDFD), we achieved the highest average R² values of 0.54, 0.62, and 0.56, respectively. Overall, this study demonstrated the potential use of environmental factors for alfalfa yield and quality estimation in-field before harvesting. However, the Sentinel-1 radar backscattering coefficients did not make significant contributions to improving the estimation performance, compared to the environmental factors. Full article

Subsoiling tillage breaks up the shallow plow layer and thickened plow pan resulting from prolonged crop rotation, thus enhancing the soil tillage layer environment and fostering crop growth. However, these changes in tillage practices are not accompanied by corresponding advancements in irrigation technology. Therefore, this study compared drip irrigation (DI) and micro-sprinkler irrigation (MS) with three watering levels (H, M, L) based on soil water content (70%, 60%, 50% of field capacity) against traditional surface irrigation (CK, 70%FC) to find the most suitable irrigation approach for subsoiling wheat fields. This study found that adjusting irrigation methods and regimes significantly impacted wheat growth and yield. Drip irrigation boosts winter wheat grain yield, harvest index, biomass transfer amount, biomass transfer rate, nitrogen accumulation, nitrogen use efficiency, and nitrogen harvest index significantly compared to surface and micro-sprinkler methods. Drip irrigation, notably the DI-M treatment, significantly enhances winter wheat grain yield by 28.7% compared to CK. Drip irrigation produced optimal results when soil water levels decreased to 60% of the field capacity. This suggests adopting a combination of DI, with irrigation initiated at 60% of field capacity, for enhanced wheat production and resource efficiency. Full article

A field study was conducted to assess the effect of tillage systems (TSs) and manure rates (MRs) on sunflower growth and yield at the University of Limpopo Experimental Farm (Syferkuil) which is on sandy loam soils and University of Venda Experimental Farm (UNIVEN) clayey soils, both located in Limpopo Province of South Africa for 2021/2022 and 2022/2023 cropping seasons. The experimental design was a split plot with three replications. The main plot was the tillage treatments: conventional (CON) and in-field rainwater harvesting (IRWH), while the subplots were the manure treatments: viz. poultry and cattle manures at rates of 20 and 35 t ha⁻¹⁰, plus a control (no manure application). The IRWH is a tillage technique that collects rainwater on a 2 m wide runoff strip into the 1 m wide basin where it infiltrates deep into the soil beyond the evaporation zone but is available for crop use. The results revealed that at Syferkuil IRWH had a significant increase (p < 0.05) on grain yield, head diameter, head dry matter and aboveground dry matter yield in both cropping seasons, whereas at UNIVEN, the significant increase was obtained on grain yield, head diameter, aboveground dry matter, plant height and stem girth during both cropping seasons. The effect of manure rate significantly increased with the application rate, with poultry manure at the highest rate of 35 t ha⁻¹ significantly recording high mean values of grain yield, head diameter, head dry matter, aboveground dry matter, plant height and stem girth at both sites during the two cropping seasons. The increase in leaf area index and 100 seed weight by IRWH and manure rate application varied across the growing stages and cropping seasons with no consistent trend. At Syferkuil, TS and MR interaction was significant on head diameter and on aboveground dry matter at flowering stage in the first cropping season, whereas at UNIVEN, it was significant on head diameter in the first cropping season. Therefore, these results suggest that IRWH combined with poultry manure (35 t ha⁻¹) can be adopted to improve sunflower crop yield under similar management and environmental conditions. In the absence of poultry manure, farmers may opt to use cattle manure at a rate of 35 t ha⁻¹ for better improved yield. Full article

This study introduces a novel methodology for the dynamic extraction of information on cotton growth in terms of height utilizing the DJI Zenmuse L1 LiDAR sensor mounted onto a DJI Matrice 300 RTK Unmanned Aerial Vehicle (UAV), aimed at enhancing the precision and efficiency of growth monitoring within the realm of precision agriculture. Employing the Progressive TIN Densification (PTD) and Cloth Simulation Filter (CSF) algorithms, combined with Kriging interpolation, we generated Canopy Height Models (CHMs) to extract the cotton heights at two key agricultural sites: Zengcheng and Tumxuk. Our analysis reveals that the PTD algorithm significantly outperforms the CSF method in terms of accuracy, with its R² values indicating a superior model fit for height extraction across different growth stages (Zengcheng: 0.71, Tumxuk: 0.82). Through meticulous data processing and cluster analysis, this study not only identifies the most effective algorithm for accurate height extraction but also provides detailed insights into the dynamic growth patterns of cotton varieties across different geographical regions. The findings highlight the critical role of UAV remote sensing in enabling large-scale, high-precision monitoring of crop growth, which is essential for the optimization of agricultural practices such as precision fertilization and irrigation. Furthermore, the study demonstrates the potential of UAV technology to select superior cotton varieties by analyzing their growth dynamics, offering valuable guidance for cotton breeding and cultivation. Full article

Ear rot caused by the Fusarium species has led to a decline in maize yield and kernel quality worldwide. The changes in the population structure of pathogens and the widespread planting of susceptible maize varieties have exacerbated the occurrence and harm of ear rot in China. Therefore, it is very important to establish the species composition of Fusarium and evaluate the resistance of the main cultivated hybrids. In this study, 366 single conidial isolates of Fusarium spp. were obtained from three provinces of Northeast China. F. verticillioides, F. subglutinans, F. proliferatum, F. oxysporum, and F. graminearum species complex (FGSC) were identified, with F. verticillioides being the most prevalent with a frequency of 44.0%. Based on the TEF-1α gene sequences analysis, the FGSC populations consisted of two independent species: F. boothii and F. graminearum, which account for 23.8% and 5.7% of the total isolates, respectively. Additionally, the resistance to ear rot by 97 maize hybrids commonly planted in Northeast China was evaluated by inoculation with F. verticillioides during 2021 and 2022. The results showed that the disease parameters of different hybrids varied significantly (p < 0.05). Approximately half of the hybrids had damage rates ranging from 0 to 15%, and 79.4% of the hybrids had a severity rating of less than 5.5. In total, 49 (50.5%) hybrids were rated as moderately resistant, which was the dominant resistance category, and 71 hybrids (73.2%) were identified as moderately to highly resistant to ear rot. Current research confirms that Fusarium ear rot in maize is mainly caused by F. verticillioides in Northeast China, and many hybrids are resistant to the disease. This study will guide growers to scientifically deploy resistant commercial hybrids to control ear rot. Full article

This study, employing the AquaCrop model, demonstrated notable efficacy in assessing and predicting crop yields for winter wheat, maize, winter rapeseed, and sugar beets in the Joint Experiment for Crop Assessment and Monitoring (JECAM) test area of Poland from 2018 to 2023. In-situ measurements, conducted through field campaigns, included parameters such as electromagnetic radiation reflectance, Leaf Area Index (LAI), soil moisture, accumulated photosynthetically active radiation, chlorophyll content, and plant development phase. The model was calibrated with input data covering daily climatic parameters from the ERA5-land Daily Aggregated repository, crop details, and soil characteristics. Specifically, for winter wheat, the Root Mean Square Error (RMSE) values ranged from 1.92% to 14.26% of the mean yield per hectare. Maize cultivation showed RMSE values ranging from 0.21% to 1.41% of the mean yield per hectare. Winter rapeseed exhibited RMSE values ranging from 0.58% to 17.15% of the mean yield per hectare. In the case of sugar beets, the RMSE values ranged from 0.40% to 1.65% of the mean yield per hectare. Normalized Difference Vegetation Index (NDVI)-based predictions showed higher accuracy for winter wheat, similar accuracy for maize and sugar beets, but lower accuracy for winter rapeseed compared to Leaf Area Index (LAI). The study contributes valuable insights into agricultural management practices and facilitates decision-making processes for farmers in the region. Full article

Supply chain disruptions, a pandemic, and war in Ukraine have exposed faultlines in a globalised food system that depends on a few staple crops grown in a few exporting regions and transported to consumers around the world. In the UK, just three crops, (wheat, barley, and oilseed rape), account for 75 per cent of the UK’s 4.5 million hectares of arable land whilst the country imports around half its food—nearly 40 per cent—from just four EU countries (The Netherlands, Ireland, Germany, and France). Poor diets contribute to one in seven deaths in the UK, 63 per cent of the population is overweight or obese and health inequality is increasing between the poorest and most affluent regions. The food security and health of the UK population is therefore dependent on a small number of locally grown crops, vulnerable supply chains, and an unhealthy, obesogenic diet. The UK food system must diversify if it is to become food and nutritionally secure, meet its climate and biodiversity goals and have a healthy and active population. Climate-resilient and nutritious underutilised crops can help diversify the UK agrifood system, but research and investment in them is sporadic, piecemeal, and unfocused. In this paper, we compare two approaches to identifying potentially suitable underutilised crops for the UK. The first, based on UK Department for Environment, Food and Rural Affairs (Defra) Project CH0224, was delivered through literature and database searches and the expertise of growers, advisers, breeders, seed suppliers, processors, traders, and researchers. The second used the CropBASE digital knowledge base for underutilised crops. The two approaches produced no single crop that was common to both shortlists. We propose that the analytical and predictive tools derived from CropBASE could be combined with local knowledge and expertise from the Defra project to provide a common framework for the identification of underutilised crops that are best suited to local UK circumstances now and in climates of the future. Full article

The research conducted at the Shanxi Agricultural University’s Quinoa Experimental Model Base in Jinzhong, Shanxi Province, aimed to assess agronomic traits and their correlation with yield across 32 quinoa varieties. Three distinct yield categories emerged: low (≤1500 kg ha⁻¹), middle (1500–2500 kg⁻¹), and high (>2500 kg ha⁻¹). High-yielding varieties demonstrated notable characteristics, including decreased plant height and increased leaf area per plant at maturity compared to low- and middle-yielding varieties. Moreover, the decline in leaf area per plant and root traits from flowering to maturity was less pronounced in the high-yielding varieties. The high-yielding varieties had a higher hardness of the stem base and middle stem by 12–13.7% and 6.3–11.5% compared to the medium- and low-yield varieties. Furthermore, high-yielding varieties indicated improvements in dry matter accumulation, decreased effective branch number, and increased main ear length and 1000-grain weight. Correlation analysis highlighted significant relationships between grain weight, yield, post-flowering senescence, and root and leaf characteristics. Structural equation model analysis revealed the negative impact of certain root and leaf traits on grain weight and yield, suggesting their importance in determining productivity. Notably, high-yielding varieties exhibited traits conducive to increased grain weight, including shorter plant height, slower root senescence, and enhanced post-flowering leaf resilience. These findings showed that understanding the relationship between agronomic traits and yield potential is crucial for optimizing quinoa production and promoting the sustainable development of this essential crop. Full article

In August 2020, the unusual appearance of crown gall symptoms was observed on the tobacco plants (hybrid PVH2310) grown in fields in the Golubinci (Srem district, Serbia) locality. The causal agent isolated from galls located on tobacco roots formed circular, convex, and glistening light blue colonies, and then dark to olive-green-colored bacterial colonies on a semi-selective D1 medium. Molecular analysis based on multiplex PCR and multi-locus sequence analysis (MLSA) using concatenated sequences of the atpD, dnaK, glnA, and rpoB genes as well as 16S rRNA identified Serbian tobacco isolates such as Agrobacterium tumefaciens (biovar 1). Two duplex PCR methods confirmed the presence of the virD2 and virC genes in tobacco isolates. Pathogenicity tests performed on carrot discs and squash fruits resulted in tumor/gall formation after 12 to 16 days post inoculation, respectively. Pathogenicity was also confirmed on tobacco plants, where isolates caused tumor development 21−25 days after inoculation. API 50 CH generated results regarding the biochemical features of the Serbian tobacco isolates. As A. tumefaciens (biovar 1) as a cause of tobacco crown gall has previously been documented solely in Japan, there is presently no data on its wider occurrence. Therefore, this first detailed investigation of A. tumefaciens isolated from naturally infected tobacco in Serbia will contribute to a better understanding of it at the global level. Full article

Intercropping soybean in tea plantations is a sustainable cultivation system that can improve the growing environment of tea plants compared to monoculture tea. However, the effects of this system on the photosynthesis activity of tea seedlings have yet to be reported. Therefore, we used tea cultivar ‘Zhongcha108’ as experimental materials to investigate the effects of intercropping soybean on the canopy spectral parameters and photosynthesis activity of tea seedlings. Canopy spectral reflectance data showed that soybean–tea intercropping (STS) improved the reflectance of 720, 750 and 840 nm bands in tea seedlings’ canopy. The vegetation indexes (VIs) value related to photosynthetic pigments in STS was obviously higher than monoculture tea (T). In addition, the F_v/F_m and SPAD value in STS were also clearly higher. Transcriptome analysis data indicated that STS induced the expression of light-harvesting complex (LHC) genes, photosystem subunit (Psbs and Psas) genes and dark reaction biological process genes (FBP1, RPE, Calvin cycle protein CP12-1 and transketolase). These results indicate that STS enhanced the photosynthesis activity. The metabolome analysis showed that STS promoted the accumulation of carbohydrate metabolites, which further provided evidence for the enhancement of photosynthesis in the leaves of tea seedlings. This study enhanced our understanding of how intercropping soybeans in a young tea plantation improves the photosynthesis activity to promote tea seedlings’ growth and development. Full article

Water scarcity is one of the significant constraints on sustainable agricultural development in arid and semi-arid regions. The challenges faced in forage production are even more severe than those encountered with general crops. The industry still struggles to achieve water-efficient, high-yield quality forage in water-scarce pastoral areas. This study focuses on alfalfa, a high-quality forage crop, employing a combination of “subsurface drip irrigation (SDI) + alternate partial root-zone irrigation (APRI)” and establishing three water supply gradients (full irrigation, 75% deficit, 50% deficit), in comparison with the widely used subsurface drip irrigation, to study the effects of two irrigation methods and three moisture gradients on alfalfa. The aim is to provide some theoretical basis and data support for achieving water-saving and high-yield quality forage in water-scarce pastoral areas. The main findings are as follows: First, compared with SDI, the two-year alternate dry and wet environment provided by alternate partial root-zone drip irrigation (ARDI) significantly increased the specific root length, specific surface area, and root length density of alfalfa at 20~40 cm depth, increasing by 33.3~76.8%, 6.4~32.97%, and 15.2~93.9%, respectively, compared to SDI. Under ARDI irrigation, the alfalfa root system has a greater contact area with the soil, which lays a solid foundation for the water and nutrient supply needed for the accumulation of its above-ground biomass. Secondly, over the two-year production process, the plant height of alfalfa under ARDI treatment was 12~14.5% higher than that under SDI, the total fresh forage yield was 43.5~64% higher, and the total dry forage yield was 23.2~33.8% higher than SDI. Under ARDI, the 75% water deficit treatment could still maintain the plant height and stem thickness of alfalfa compared to full irrigation with SDI and increased the dry forage yield by 6.6% without significantly reducing the quality, significantly enhancing the productive performance of alfalfa. Moreover, during the two years of production and utilization, the nutritional quality of alfalfa under the ARDI irrigation mode did not significantly decrease compared to SDI, maintaining the stable nutritional quality of alfalfa over multiple years of production. Lastly, thanks to the improved root system and increased yield of alfalfa under ARDI irrigation, and based on this, its water evapotranspiration did not significantly increase compared to SDI; the annual average Alfalfa Water Productivity Index (AWP_I) and Alfalfa Water Productivity of Crop (AWP_C) under ARDI irrigation increased by 28.8% and 37.2%, respectively, improving the water use efficiency of alfalfa production. In summary, in the production of alfalfa in water-scarce pastoral areas, ARDI and its water deficit treatment have more potential for water-saving than SDI as a water-saving irrigation strategy. Full article

The limited culinary utilizations of durum wheat (Triticum turgidum ssp. durum) are partly related to its very hard kernel texture, which is due to the softness genes Puroindoline a (Pina) and Puroindoline b (Pinb) on the Hardness (Ha) locus eliminated during allopolyploid formation. A previous study has reported that the softness genes Dina/Dinb, homologous to Pina/Pinb, were located on the chromosome arm 5VS of wild species Dasypyrum villosum. In the present study, we describe the process of transferring the soft grain texture from D. villosum into durum wheat through homoeologous recombination to develop a Robertsonian translocation. A durum wheat–D. villosum T5AL·5V#5S translocation line, S1286, was developed and characterized by molecular cytogenetic analysis from BC₄F₂ progeny of durum cv. ZY1286/D. villosum 01I140. The translocation line S1286 exhibited a soft grain texture as evidenced by observation through an electron microscope and a Single Kernel Characterization System (SKCS) hardness value of 5.5. Additionally, a newly developed 5VS/5AS co-dominant InDel marker, LW5VS-1, facilitated the transfer of the T5AL·5V#5S translocated chromosome into diverse durum wheat backgrounds. Subsequently, the T5AL·5V#5S translocated chromosome was transferred into five high-yielding durum wheat backgrounds by backcrossing and traced using marker LW5VS-1. Compared with each recurrent parent, T5AL·5V#5S lines showed good viability, similar development, and no yield penalty. Meanwhile, a significant decrease in plant height of about 6.0% was observed when comparing T5AL·5V#5S translocation lines with their recurrent parents. Accordingly, our results provide an efficient strategy for developing soft kernel durum wheat through the combination of T5AL·5V#5S translocation and the co-dominant marker LW5VS-1, which will be crucial for meeting the future challenges of sustainable agriculture and food security. Full article

The consistently low yield turnout of maize on farmers’ fields owing to drought and the nutritional challenges attributable to the consumption of white endosperm maize pose a major threat to food and nutritional security in Sub-Saharan Africa (SSA). The objectives of this study were to assess the performance of newly developed extra-early maturing orange hybrids under managed drought and well-watered conditions, compare the outcomes of multiple-trait base index and multi-trait genotype–ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety orange hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14 × 14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions, suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple-trait base index and the multi-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA. Full article